Parameter derivation for intra prediction

Abstract

A method for video processing is provided. The method includes determining, for a conversion between a current video block of a video and a coded representation of the video, a context that is used to code a flag using arithmetic coding in the coded representation of the current video block, wherein the context is based on whether a top-left neighboring block of the current video block is coded using a cross-component linear model (CCLM) prediction mode; and performing the conversion based on the determining.

What is claimed is: 
     
       1. A method of processing video data, comprising:
 determining, for a conversion between a current video block of a video and a bitstream of the video, parameters for a linear model prediction or cross-color component prediction based on refined neighboring luma samples and chroma samples of the current video block; 
 deriving prediction values of a chroma component of the current video block based on the parameters and refined internal luma samples of the current video block; and 
 performing the conversion based on the prediction values; 
 wherein the refined neighboring luma samples and the refined internal luma samples of the current video block are determined by down-sampling neighboring luma samples and internal luma samples followed by a non-linear process; 
 wherein the parameters for the linear model prediction are α and β, wherein α=(C1−C0)/(L1−L0) and β=C0−αL0, wherein C0 and C1 are derived from neighboring chroma samples, and wherein L0 and L1 are derived from neighboring luma samples; 
 wherein C0 and L0 are based on S neighboring chroma and luma samples, denoted {Cx1, Cx2, . . . , CxS} and {Lx1, Lx2, . . . , LxS}, respectively, wherein C1 and L1 are based on T neighboring chroma and luma samples, denoted {Cy1, Cy2, . . . , CyT} and {Ly1, Ly2, . . . , LyT}, respectively, wherein S=T, 
 wherein {Cx1, Cx2, . . . , CxS} are corresponding to {Lx1, Lx2, . . . , LxS}, 
 wherein {Cy1, Cy2, . . . , CyT} are corresponding to {Ly1, Ly2, . . . , LyT}, 
 wherein C0=f0(Cx1, Cx2, . . . , CxS), L0=f1(Lx1, Lx2, . . . , LxS), C1=f2(Cy1, Cy2, . . . , CyT) and L1=f3(Ly1, Ly2, . . . , LyT), and 
 wherein f0, f1, f2 and f3 are functions. 
 
     
     
       2. The method of  claim 1 , wherein f0 and f1 are a first function. 
     
     
       3. The method of  claim 1 , wherein f2 and f3 are a second function. 
     
     
       4. The method of  claim 1 , wherein f0, f1, f2 and f3 are a third function, wherein the third function is an averaging function. 
     
     
       5. The method of  claim 1 , wherein {Lx1, Lx2, . . . , LxS} are the smallest samples of a group of luma samples, and {Ly1, Ly2, . . . , LyT} are the largest samples of a group of luma samples,
 wherein the group of luma samples comprises all neighboring samples used in VTM-3.0 to derive the parameters of the linear model prediction; or 
 the group of luma samples comprises a subset of neighboring samples used in VTM-3.0 to derive the parameters of the linear model prediction, and wherein the subset is not identical to all the neighboring samples. 
 
     
     
       6. The method of  claim 1 , wherein parameters for the linear model prediction or cross-color component prediction is further determined by selecting neighboring samples based on a position of a largest or a smallest neighboring sample. 
     
     
       7. The method of  claim 6 , wherein the largest neighboring sample is located at a position (x0, y0), samples in a region (x0−d1, y0), (x0, y0−d2), (x0+d3, y0), (x0, y0+d4) are utilized to select the neighboring samples, and wherein{d1, d2, d3, d4} depend on the position (x0, y0); and
 the smallest neighboring sample is located at a position (x1, y1), samples in a region (x1−d1, y1), (x1, y1−d2), (x1+d3, y1), (x1, y1+d4) are utilized to select the neighboring samples, and {d1, d2, d3, d4} depend on the position (x1, y1), 
 wherein the neighboring samples represent a color component. 
 
     
     
       8. The method of  claim 1 , wherein parameters for the linear model prediction or cross-color component prediction is further determined based on a main color component and a dependent color component, the main color component selected as one of a luma color component and a chroma color component and the dependent color component selected as the other of the luma color component and the chroma color component. 
     
     
       9. The method of  claim 1 , further comprising:
 determining a context that is used to code a flag using arithmetic coding in the bitstream of the current video block, wherein the context is based on whether a top-left neighboring block of the current video block is coded using a cross-component linear model (CCLM) prediction mode, wherein the flag is signaled to indicate whether the CCLM prediction mode is applied on the current video block, and 
 wherein the CCLM prediction mode uses a linear mode to derive prediction values of a chroma component from another component. 
 
     
     
       10. The method of  claim 9 , wherein the context comprise a first context of the top-left neighboring block uses the CCLM prediction mode and comprises a second context different from the first context if the top-left neighboring block does not use the CCLM prediction mode. 
     
     
       11. The method of  claim 9 , wherein the top-left neighboring block is unavailable, and wherein the CCLM prediction mode is considered to be enabled; optionally the top-left neighboring block is unavailable, and wherein the CCLM prediction mode is considered to be disabled; optionally the top-left neighboring block is intra-coded, and wherein the CCLM prediction mode is considered to be enabled; optionally the top-left neighboring block is intra-coded, and wherein the CCLM prediction mode is considered to be disabled. 
     
     
       12. The method of  claim 1 , further comprising:
 determining a coding order for one or more indications of a derived mode (DM mode) and a linear mode (LM mode) based on a coding mode of one or more neighboring blocks of the current video block, 
 wherein the LM mode uses a linear mode to derive prediction values of a chroma component from another component, and the DM mode derives intra prediction mode of a chroma component from another component. 
 
     
     
       13. The method of  claim 12 , wherein a top-left neighboring block of the one or more neighboring blocks is coded with the LM mode, and wherein an indication of the LM mode is coded first; optionally a top-left neighboring block of the one or more neighboring blocks is coded with the DM mode, and wherein an indication of the DM mode is coded first; optionally a top-left neighboring block of the one or more neighboring blocks is coded with a coding mode that is different from the LM mode, and wherein an indication of the DM mode is coded first,
 wherein the one or more indications are signaled in a sequence parameter set (SPS), a video parameter set (VPS), a picture parameter set (PPS), a picture header, a slice header, a tile group header, one or more largest coding units or one or more coding units. 
 
     
     
       14. The method of  claim 1 , wherein the conversion includes encoding the current video block into the bitstream. 
     
     
       15. The method of  claim 1 , wherein the conversion includes decoding the current video block from the bitstream. 
     
     
       16. An apparatus for processing video data, comprising a processor and a non-transitory memory with instructions thereon, wherein the instructions upon execution by the processor, cause the processor to:
 determine, for a conversion between a current video block of a video and a bitstream of the video, parameters for a linear model prediction or cross-color component prediction based on refined neighboring luma samples and chroma samples of the current video block; 
 derive prediction values of a chroma component of the current video block based on the parameters and refined internal luma samples of the current video block; and 
 perform the conversion based on the prediction values; 
 wherein the refined neighboring luma samples and the refined internal luma samples of the current video block are determined by down-sampling neighboring luma samples and internal luma samples followed by a non-linear process wherein the parameters for the linear model prediction are α and β, wherein α=(C1−C0)/(L1−L0) and β=C0−αL0, wherein C0 and C1 are derived from neighboring chroma samples, and wherein L0 and L1 are derived from neighboring luma samples; 
 wherein C0 and L0 are based on S neighboring chroma and luma samples, denoted {Cx1, Cx2, . . . , CxS} and {Lx1, Lx2, . . . , LxS}, respectively, wherein C1 and L1 are based on T neighboring chroma and luma samples, denoted {Cy1, Cy2, . . . , CyT} and {Ly1, Ly2, . . . , LyT}, respectively, wherein S=T, 
 wherein {Cx1, Cx2, . . . , CxS} are corresponding to {Lx1, Lx2, . . . , LxS}, 
 wherein {Cy1, Cy2, . . . , CyT} are corresponding to {Ly1, Ly2, . . . , LyT}, 
 wherein C0=f0(Cx1, Cx2, . . . , CxS), L0=f1(Lx1, Lx2, . . . , LxS), C1=f2(Cy1, Cy2, . . . , CyT) and L1=f3(Ly1, Ly2, . . . , LyT), and 
 wherein f0, f1, f2 and f3 are functions. 
 
     
     
       17. A non-transitory computer-readable recording medium storing a bitstream of a video which is generated by a method performed by a video processing apparatus, wherein the method comprises:
 determining, for a conversion between a current video block of the video and the bitstream of the video, parameters for a linear model prediction or cross-color component prediction based on refined neighboring luma samples and chroma samples of the current video block; 
 deriving prediction values of a chroma component of the current video block based on the parameters and refined internal luma samples of the current video block; and 
 generating the bitstream based on the prediction values; 
 wherein the refined neighboring luma samples and the refined internal luma samples of the current video block are determined by down-sampling neighboring luma samples and internal luma samples followed by a non-linear process wherein the parameters for the linear model prediction are α and β, wherein α=(C1−C0)/(L1−L0) and β=C0−αL0, wherein C0 and C1 are derived from neighboring chroma samples, and wherein L0 and L1 are derived from neighboring luma samples; 
 wherein C0 and L0 are based on S neighboring chroma and luma samples, denoted {Cx1, Cx2, . . . , CxS} and {Lx1, Lx2, . . . , LxS}, respectively, wherein C1 and L1 are based on T neighboring chroma and luma samples, denoted {Cy1, Cy2, . . . , CyT} and {Ly1, Ly2, . . . , LyT}, respectively, wherein S=T, 
 wherein {Cx1, Cx2, . . . , CxS} are corresponding to {Lx1, Lx2, . . . , LxS}, 
 wherein {Cy1, Cy2, . . . , CyT} are corresponding to {Ly1, Ly2, . . . , LyT}, 
 wherein C0=f0(Cx1, Cx2, . . . , CxS), L0=f1(Lx1, Lx2, . . . , LxS), C1=f2(Cy1, Cy2, . . . , CyT) and L1=f3(Ly1, Ly2, . . . , LyT), and 
 wherein f0, f1, f2 and f3 are functions. 
 
     
     
       18. The apparatus of  claim 16 , wherein f0 and f1 are a first function. 
     
     
       19. The apparatus of  claim 16 , wherein f2 and f3 are a second function. 
     
     
       20. The apparatus of  claim 16 , wherein f0, f1, f2 and f3 are a third function, wherein the third function is an averaging function.